DE102020213289A1 - Bildverarbeitungssystem - Google Patents

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Publication number
DE102020213289A1
DE102020213289A1 DE102020213289.5A DE102020213289A DE102020213289A1 DE 102020213289 A1 DE102020213289 A1 DE 102020213289A1 DE 102020213289 A DE102020213289 A DE 102020213289A DE 102020213289 A1 DE102020213289 A1 DE 102020213289A1
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Prior art keywords
image
neural network
post
processed
processing system
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Pending
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DE102020213289.5A
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German (de)
English (en)
Inventor
Tae Hyun Kim
Jin Su Kim
Jong Hyun BAE
Sung Joo Hong
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SK Hynix Inc
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SK Hynix Inc
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Publication of DE102020213289A1 publication Critical patent/DE102020213289A1/de
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    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T1/00—General purpose image data processing
    • G06T1/20—Processor architectures; Processor configuration, e.g. pipelining
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N20/00—Machine learning
    • G06N20/20—Ensemble learning
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/04—Architecture, e.g. interconnection topology
    • G06N3/045—Combinations of networks
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/04—Architecture, e.g. interconnection topology
    • G06N3/0464—Convolutional networks [CNN, ConvNet]
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/04—Architecture, e.g. interconnection topology
    • G06N3/047—Probabilistic or stochastic networks
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/04—Architecture, e.g. interconnection topology
    • G06N3/0475—Generative networks
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/08—Learning methods
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/08—Learning methods
    • G06N3/088—Non-supervised learning, e.g. competitive learning
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/08—Learning methods
    • G06N3/094—Adversarial learning
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T5/00—Image enhancement or restoration
    • G06T5/50—Image enhancement or restoration using two or more images, e.g. averaging or subtraction
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T5/00—Image enhancement or restoration
    • G06T5/60—Image enhancement or restoration using machine learning, e.g. neural networks
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/70—Arrangements for image or video recognition or understanding using pattern recognition or machine learning
    • G06V10/764—Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/70—Arrangements for image or video recognition or understanding using pattern recognition or machine learning
    • G06V10/82—Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/20—Special algorithmic details
    • G06T2207/20081—Training; Learning
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/20—Special algorithmic details
    • G06T2207/20084—Artificial neural networks [ANN]

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  • Engineering & Computer Science (AREA)
  • Theoretical Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Evolutionary Computation (AREA)
  • Software Systems (AREA)
  • Artificial Intelligence (AREA)
  • Computing Systems (AREA)
  • General Health & Medical Sciences (AREA)
  • Health & Medical Sciences (AREA)
  • Data Mining & Analysis (AREA)
  • General Engineering & Computer Science (AREA)
  • Mathematical Physics (AREA)
  • Computational Linguistics (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Biomedical Technology (AREA)
  • Biophysics (AREA)
  • Molecular Biology (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Medical Informatics (AREA)
  • Multimedia (AREA)
  • Databases & Information Systems (AREA)
  • Probability & Statistics with Applications (AREA)
  • Image Analysis (AREA)
  • Image Processing (AREA)
DE102020213289.5A 2019-10-29 2020-10-21 Bildverarbeitungssystem Pending DE102020213289A1 (de)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
KR1020190135041A KR20210050684A (ko) 2019-10-29 2019-10-29 이미지 처리 시스템
KR10-2019-0135041 2019-10-29

Publications (1)

Publication Number Publication Date
DE102020213289A1 true DE102020213289A1 (de) 2021-04-29

Family

ID=75378970

Family Applications (1)

Application Number Title Priority Date Filing Date
DE102020213289.5A Pending DE102020213289A1 (de) 2019-10-29 2020-10-21 Bildverarbeitungssystem

Country Status (5)

Country Link
US (1) US11599981B2 (https=)
JP (1) JP2021072106A (https=)
KR (1) KR20210050684A (https=)
CN (1) CN112750067B (https=)
DE (1) DE102020213289A1 (https=)

Families Citing this family (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US12235651B1 (en) * 2021-03-29 2025-02-25 Amazon Technologies, Inc. Autonomous navigation correction system
KR102728337B1 (ko) * 2021-05-31 2024-11-11 한국전자기술연구원 Gan 구조를 활용한 영상 영역 분할 방법 및 시스템

Family Cites Families (30)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US10169662B2 (en) 2015-06-15 2019-01-01 Google Llc Remote biometric monitoring system
US10460231B2 (en) 2015-12-29 2019-10-29 Samsung Electronics Co., Ltd. Method and apparatus of neural network based image signal processor
JP6463512B2 (ja) 2016-05-24 2019-02-06 オリンパス株式会社 画像信号処理装置、画像信号処理方法および画像信号処理プログラム
US10602126B2 (en) * 2016-06-10 2020-03-24 Lucid VR, Inc. Digital camera device for 3D imaging
KR101961177B1 (ko) 2016-07-22 2019-03-22 한국과학기술원 뉴럴 네트워크를 이용한 영상 처리 방법 및 장치
WO2018053340A1 (en) 2016-09-15 2018-03-22 Twitter, Inc. Super resolution using a generative adversarial network
KR101791573B1 (ko) 2016-10-21 2017-10-31 서강대학교산학협력단 컨볼루션 신경망을 이용한 비디오 스트림에 대한 수퍼 해상도 장치 및 방법
US10803378B2 (en) 2017-03-15 2020-10-13 Samsung Electronics Co., Ltd System and method for designing efficient super resolution deep convolutional neural networks by cascade network training, cascade network trimming, and dilated convolutions
US10262236B2 (en) * 2017-05-02 2019-04-16 General Electric Company Neural network training image generation system
US10497257B2 (en) * 2017-08-31 2019-12-03 Nec Corporation Parking lot surveillance with viewpoint invariant object recognition by synthesization and domain adaptation
US10430937B2 (en) * 2017-09-25 2019-10-01 United Technologies Corporation Automated material characterization system including conditional generative adversarial networks
US11188783B2 (en) * 2017-10-19 2021-11-30 Nokia Technologies Oy Reverse neural network for object re-identification
US10467501B2 (en) * 2017-10-30 2019-11-05 Sap Se Computer vision architecture with machine learned image recognition models
US10936863B2 (en) * 2017-11-13 2021-03-02 Way2Vat Ltd. Systems and methods for neuronal visual-linguistic data retrieval from an imaged document
CN107909621A (zh) * 2017-11-16 2018-04-13 深圳市唯特视科技有限公司 一种基于双生成对抗网络的医学图像合成方法
CN108257116A (zh) * 2017-12-30 2018-07-06 清华大学 一种生成对抗图像的方法
US10944767B2 (en) * 2018-02-01 2021-03-09 International Business Machines Corporation Identifying artificial artifacts in input data to detect adversarial attacks
US10748314B2 (en) * 2018-02-15 2020-08-18 Microsoft Technology Licensing, Llc Controllable conditional image generation
US10552714B2 (en) * 2018-03-16 2020-02-04 Ebay Inc. Generating a digital image using a generative adversarial network
US20190297326A1 (en) * 2018-03-21 2019-09-26 Nvidia Corporation Video prediction using spatially displaced convolution
US10825219B2 (en) * 2018-03-22 2020-11-03 Northeastern University Segmentation guided image generation with adversarial networks
US11100632B2 (en) * 2018-04-13 2021-08-24 Elekta, Inc. Image synthesis using adversarial networks such as for radiation therapy
CN108764091B (zh) * 2018-05-18 2020-11-17 北京市商汤科技开发有限公司 活体检测方法及装置、电子设备和存储介质
CN108932527A (zh) * 2018-06-06 2018-12-04 上海交通大学 使用交叉训练模型检测对抗样本的方法
CN109036389A (zh) * 2018-08-28 2018-12-18 出门问问信息科技有限公司 一种对抗样本的生成方法及装置
CN109685200B (zh) * 2018-11-19 2023-04-25 华东师范大学 基于生成对抗网络的雾计算工业协议构建方法及构建系统
JP2022526718A (ja) * 2019-03-14 2022-05-26 ハイパーファイン，インコーポレイテッド 空間周波数データから磁気共鳴画像を生成するための深層学習技術
CN110222774A (zh) * 2019-06-10 2019-09-10 百度在线网络技术（北京）有限公司 非法图像鉴别方法、装置、内容安全防火墙及存储介质
CN110322396B (zh) * 2019-06-19 2022-12-23 怀光智能科技（武汉）有限公司 一种病理切片颜色归一化方法及系统
US11126891B2 (en) * 2019-09-11 2021-09-21 Toyota Research Institute, Inc. Systems and methods for simulating sensor data using a generative model

Also Published As

Publication number Publication date
KR20210050684A (ko) 2021-05-10
US20210125320A1 (en) 2021-04-29
CN112750067B (zh) 2024-05-07
CN112750067A (zh) 2021-05-04
US11599981B2 (en) 2023-03-07
JP2021072106A (ja) 2021-05-06

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